With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.

翻译：随着ChatGPT等大型人工智能模型的广泛应用，AI生成内容（AIGC）日益受到关注，并正在引领内容创建和知识表征领域的范式转变。AIGC利用生成式大规模AI算法，基于用户提供的提示，以更快的速度和更低的成本辅助或替代人类创建大规模、高质量且类人化的内容。尽管近期AIGC取得了显著进展，但安全、隐私、伦理和法律挑战仍需解决。本文对AIGC范式的工作原理、安全与隐私威胁、现有解决方案及未来挑战进行了深入综述。具体而言，我们首先探讨了AIGC的使能技术与通用架构，并讨论了其工作模式与关键特征；然后，我们研究了AIGC安全与隐私威胁的分类体系，并强调了GPT及AIGC技术的伦理与社会影响；此外，我们回顾了面向可监管AIGC范式的现有AIGC水印方法（涵盖AIGC模型及其生成内容）；最后，我们指出了与AIGC相关的未来挑战及开放研究方向。